Build a deeper understanding of complex environments and how to derive an advantage from them.

Four AI business courses compose the programme:

Data Science for Business

AI Business Intelligence

Business Textual Learning

Business Network intelligence

Data Science for Business

Dates

Monday 11th MAY – Friday 15th MAY 2020

Students will be expected to arrive in Rennes on Sunday 10th at the latest and leave on the 15tt evening at the earliest.

Programme

This module starts with the very basics of Python coding and works up modern advanced techniques such as machine learning and deep learning. The field of data science for business is the context for the class, and so applied business examples are the focus. The module is very practical – you will follow the lessons using shared Python codebooks and implement the techniques along with the professor.

Topics covered

Learn Python from the very beginning

Master machine learning for business

Understand AI deep learning techniques

Apply learning to real business datasets

Pre-requisites

Sucessful completion of at least two years of undergraduate level studies

Strong command of spoken and written English

AI Business Intelligence

Dates

Monday 18th MAY – Saturday 23rd MAY 2020 (Thursday 21st May 2020 is a bank holiday)

Students will be expected to arrive in Rennes on Sunday 17th at the latest and leave on the 23rd evening at the earliest.

Programme

In business data science we take business data and create business intelligence. This module focuses on the creation and presentation of that business intelligence. You will work primarily on Tableau (for which a personal license will be provided to you), the leading intelligence generation and visualization platform in modern business.

Topics covered

Develop expert Tableau knowledge

Apply Python for data visualisation

Understand business intelligence needs

Generate automated BI reporting

Pre-requisites

Sucessful completion of at least two years of undergraduate level studies.

Coding experience or attend the «Data Science for Business» class before

Strong command of spoken and written English

Business Textual Learning

Dates

Monday 25th MAY – Friday 29th MAY 2020

Students will be expected to arrive in Rennes on the 24th May at the latest and leave on the 29th May evening at the earliest

Programme

How to automate creating knowledge from written documents is still in its infancy. Largely people still manually read documents in order to extract intelligence from them. But data science, through its natural language processing field, offers fascinating new techniques to automate generating knowledge from text. This module brings you on a journey through the practical application of the most business relevant of the techniques in this area.

Topics covered

Extract knowledge from text

Apply natural language processing

Learn new science of topic modelling

Measure text sentiment and complexity

Pre-requisite

Sucessful completion of at least two years of undergraduate level studies.

Coding experience or attend the «Data Science for Business» class before

Strong command of spoken and written English

Business Network Intelligence

Dates

Tuesday 2nd JUNE – Saturday 6th JUNE 2020 (Monday 1st JUNE 2020 is a bank holiday)

Students will be expected to arrive in Rennes on the first of June at the latest and leave on the 6th evening at the earliest.

Programme

The best businesses make effective use of their networks – such as their workforce and their external connections including customers and social media networks. They might crowdsource intelligence, customers, and funding. In this module we show how new data science techniques allow the extraction of business intelligence from the firm’s diverse networks.

Topics covered

Understand connectivity of today’s society

Analyze social and business networks

Learn network visualization techniques

Apply big data techniques and analytics

Pre-requisites

Sucessful completion of at least two years of undergraduate level studies

Coding experience or attend the «Data Science for Business» class before

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